Proceedings

Find matching any: Reset
Gobezie, T.B
Karampoiki, M
Add filter to result:
Authors
Saurette, D
Biswas, A
Gobezie, T.B
Karampoiki, M
Todman, L
Mahmood, S
Murdoch, A
Paraforos, D
Hammond, J
Ranieri, E
Topics
Precision Horticulture
Big Data, Data Mining and Deep Learning
Type
Oral
Year
2022
Home » Authors » Results

Authors

Filter results2 paper(s) found.

1. Digital Soil Sensing and Mapping for Crop Suitability

Soil, central to any land-based production system, determines the success of any crops. While soil for a farm or field is fixed, the crops can be selected to best fit the soil’s capability and production. Traditionally crops are selected based on farm history, knowledge, and years of trial and error to tailor the right crop to the right soil. Inherent challenges associated with this make the whole process unsustainable. Due to the consistent nature of the information collected, soil sensors... D. Saurette, A. Biswas, T.B. Gobezie

2. A Bayesian Network Approach to Wheat Yield Prediction Using Topographic, Soil and Historical Data

Bayesian Network (BN) is the most popular approach for modeling in the agricultural domain. Many successful applications have been reported for crop yield prediction, weed infestation, and crop diseases. BN uses probabilistic relationships between variables of interest and in combination with statistical techniques the data modeling has many advantages. The main advantages are that the relationships between variables can be learned using the model as well as the potential to deal with missing... M. Karampoiki, L. Todman, S. Mahmood, A. Murdoch, D. Paraforos, J. Hammond, E. Ranieri